1. Field of the Invention
The present invention relates to a method and a device for collating biometric information, which are used for an entrance/exit management device for managing an entrance to/an exit from a security-needed room, facilities or the like to authenticate a person based on biometric information such as a face image obtained from the person.
2. Description of the Related Art
Conventionally, for example, in the collation device for collating biometric information such as a face image, the biometric information is generally obtained from a collation target person of a stable state. This is for the purpose of obtaining the biometric information under conditions as similar as possible to those of biometric information registered as a dictionary. In other words, it is to obtain the biometric information of the same state as that at the time of registration as much as possible by suppressing fluctuation in posture (e.g., face direction) of the person or an environmental change of an illumination light or the like as much as possible that the biometric information is obtained from the collation target person of the stable state (e.g., halted state) in the conventional collation device.
Additionally, a method for authenticating a person based on biometric information obtained from a moving (e.g. walking) person has recently been proposed. For example, Jpn. Pat. Appln. KOKAI Publication No. 60-57475 (Document 1) discloses a method for collating feature data obtained from a plurality of images continuous as input images with dictionary data obtained from a plurality of images for registration stored (registered) beforehand in a storage device. According to this method, a generated subspace is stored beforehand as dictionary data (dictionary subspace) based on a feature amount obtained from the plurality of images for registration, and similarities between a subspace (input subspace) generated based on the feature amount obtained from the plurality of images as the input images and the dictionary subspace are evaluated. Such a collation method is called a mutual subspace method.
Jpn. Pat. Appln. KOKAI PUBLICATION No. 11-265452 (Document 2) or pp. 613 to 620 “Face Image Recognition Robust to Environmental Changes using Restrictive Mutual Subspace Method” by Kazuhiro Fukui, Osamu Yamaguchi, Kaoru Suzuki, and Kenichi Maeda, Journal of Institute of Electronics, Information and Communication Engineers, vol. J82-DII, No. 4 (1999) (Document 3) describes a device for collating a face image by using the method described in the Document 1.
However, the collation device of the biometric information which uses the aforementioned conventional method has the following problems.
For example, according to the aforementioned conventional collation method of biometric information such as a face image, an unnatural movement or operation must be forced on a collation target person during collation. As an example, when a face image is used as biometric information, in the conventional collation device, a face image having a face direction or the like set similar as much as possible to that during registration is obtained as an input image to increase collation accuracy. In this case, a movement to fix a face or the like while the face is directed similarly to that during registration is forced on the collation target person. As described above, if an environment such as illumination conditions for photographing an input image is different from that during registration, collation accuracy is reduced.
According to the collation method (mutual subspace method) described in each of the Documents 1 to 3, determination is made as to whether a person is identical by generating the input subspace from the input image group and evaluating the similarity between the input subspace and the dictionary subspace generated from the image group for registration. According to the collation device of a face image using such a mutual space method, by generating the dictionary subspace (dictionary data) from the face image obtained under various conditions (e.g., face direction with respect to the camera, intensity of illumination, irradiation direction, and the like), it is possible to register the dictionary data which reflects various conditions. In other words, according to the mutual subspace method, desired collation accuracy can be maintained by reflecting fluctuation of conditions (condition fluctuation likely to occur during collation) predicted to include the input image in the dictionary data.
However, in the case of collating a face image by using a moving image obtained by photographing a moving recognition target person as an input image series (collating a face image of a moving person), there is a possibility that a movement of the collation target person will become large more than expected. In such a case, as a face direction, illumination conditions and the like fluctuate more than expected, there will be more input images of conditions not reflected in dictionary data. As a result, in the collation of the face image of the moving person by the conventional method, collation accuracy is reduced because of an influence of the image of conditions included in the input image series but unpredicted during registration.